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Selection of sustainable industrial livestock site using the R-Number GIS-MCDM method: A case study of Iran

Sahar Shahrabi-Farahani, Ashkan Hafezalkotob, Davood Mohammaditabar, Kaveh Khalili‐Damghani

2024Environmental and Sustainability Indicators14 citationsDOIOpen Access PDF

Abstract

Today, the livestock industry, as a key supplier of human food resources, plays an essential role in contributing to globally adopted sustainable development goals (SDGs). General policies are needed to guide the livestock industry in an economically, socially, and environmentally sustainable manner. These policies should include sustainable development goals, considering specific spatial situations and existing risks. The initial step toward achieving sustainable development in the livestock industry involves the selection of suitable sites while considering associated risks. This study focuses on examining the ecological, economic, and social potential of Iran's Khuzestan province for livestock breeding and identifies crucial information indicators for livestock industry development. This article is one of the first articles to study industrial livestock site selection using the GIS-MCDM hybrid method with the R-numbers. This method aims to address uncertainty and prevent errors associated with fuzzy numbers. In this research, 13 suitable places for livestock development were identified. To determine the most suitable place among the candidate places, we use a hybrid decision-making framework utilizing R-number and MULTIMOORA methods. To confirm the validity of the research methods, we computed data with other methods, and all methods selected the A1 site as the most suitable place for livestock.

Topics & Concepts

LivestockMultiple-criteria decision analysisSustainable developmentBusinessSite selectionEnvironmental resource managementSelection (genetic algorithm)Environmental planningEnvironmental economicsComputer scienceGeographyOperations researchEnvironmental scienceEngineeringEconomicsEcologyPolitical scienceForestryBiologyArtificial intelligenceLawMunicipal Solid Waste ManagementSoil and Land Suitability AnalysisFacility Location and Emergency Management